Genes are at the center of nearly every human disease and symptom, and until the past few decades, medical researchers had a much narrower interpretation of the human body’s entire genetic makeup, also called the genome.
Genes are at the center of nearly every human disease and symptom, and until the past few decades, medical researchers had a much narrower interpretation of the human body’s entire genetic makeup, also called the genome.
Lila is a registered purebred beagle, but depending on what company does her DNA testing, she might be part rottweiler, part American foxhound, or not a beagle at all.
For geneticist Joanne Cole, PhD, food is life. Her love goes beyond trying a new recipe and seeking out new restaurants – it’s also in her work in the University of Colorado Department of Biomedical Informatics (DBMI), identifying the connection between genetics and nutrition.
Exploring diverse ancestry is a critical factor in furthering medical research.
A new study published in Nature Genetics from researchers in the Department of Biomedical Informatics (DBMI) at the University of Colorado School of Medicine, in partnership with the University of California San Francisco and Stanford University, is the largest of its kind that focuses on ancestry correlations with biomedical traits and the first study to examine the role of genetic variants across diverse ancestries in regulating gene expression.
Transcriptome-wide association studies have helped uncover the role of individual genes in disease-relevant mechanisms, explain researchers from the CU Department of Biomedical Informatics. However, modern models of the architecture of complex traits predict that gene-gene interactions play a crucial role in disease origin and progression. Researchers introduce PhenoPLIER, a computational approach that maps gene-trait associations and pharmacological perturbation data into a common latent representation for a joint analysis and observe that diseases are significantly associated with gene modules expressed in relevant cell types, and our approach is accurate in predicting known drug-disease pairs and inferring mechanisms of action.
After tracking calorie-control dieters and intermittent fasters for three months, both had improved microbiome diversity, said study author Maggie Stanislawski, an assistant professor in the CU Department of Biomedical Informatics.
DBMI geneticist Joanne Cole, PhD, explains the role of genetics and other factors in food preference.
Researchers in the CU Department of Biomedical Informatics evaluate associations among gut microbiota (MB), DNA methylation (DNAme), and diet prior to and during a behavioral weight loss intervention.
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